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首页> 外文期刊>4OR: A Quarterly Journal of Operations Research >Solving real-world vehicle routing problems in uncertain environments
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Solving real-world vehicle routing problems in uncertain environments

机译:解决不确定环境中的实际车辆路线问题

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摘要

This is a summary of the Ph.D. thesis defended by the author in December 2009 at École des Mines de Nantes and Universidad de los Andes in Bogotá. The thesis was advised by Christelle Guéret and Andrés L. Medaglia and co-advised by Bruno Castanier and Nubia Velasco. The manuscript is written in English and it is available from the author upon request. The focus of the dissertation is to study real-world vehicle routing problems (VRPs) in uncertain environments. First, the thesis proposes a set of new methods for the VRP faced by a public utility and reports how these methods were embedded into a decision support system. Second, the thesis introduces a stochastic VRP widely found in practice but never studied in the literature before: the multi-compartment VRP with stochastic demands (MC-VRPSD). To solve the problem the dissertation proposes a set of solution methods that offer different tradeoffs between accuracy, speed, simplicity and flexibility. Lastly, the thesis proposes two multiobjective approaches to address the risk behavior of decision makers towards the cost spread in stochastic routing problems and applies them to the MC-VRPSD.
机译:这是博士学位的总结。该论文于2009年12月由作者在波哥大的南特Écoledes Mines和洛斯安第斯大学获得辩护。这篇论文是由ChristelleGuéret和AndrésL. Medaglia提出的,并由Bruno Castanier和Nubia Velasco共同建议。手稿是用英语写的,可应要求从作者处获得。论文的重点是研究不确定环境下的真实车辆路径问题。首先,论文提出了一套面向公共事业的VRP的新方法,并报告了如何将这些方法嵌入到决策支持系统中。其次,本文介绍了一种在实践中广泛发现但以前从未在文献中研究过的随机VRP:具有随机需求的多室VRP(MC-VRPSD)。为了解决这个问题,本文提出了一套解决方法,它们在准确性,速度,简单性和灵活性之间提供了不同的权衡。最后,本文提出了两种多目标方法来解决决策者针对随机路径问题中成本分散的风险行为,并将其应用于MC-VRPSD。

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